1. Field of the Invention
The present application relates to financial data processing, in particular customer modeling and behavioral analysis.
2. Background Art
It is axiomatic that consumers will tend to spend more when they have greater purchasing power. The capability to accurately estimate a consumer's spend capacity could therefore allow a financial institution (such as a credit company, lender or any consumer services company) to better target potential prospects and identify any opportunities to increase consumer transaction volumes, without an undue increase in the risk of defaults. Consumers will be most attracted to products that are customized specifically for their individual interests and spending patterns. Attracting additional consumer spending in this manner, in turn, would increase such financial institution's revenues, primarily in the form of an increase in transaction fees and interest payments received. Consequently, a consumer model that can accurately estimate purchasing power and identify industries in which the consumer is most interested in spending is of paramount interest to many financial institutions and other consumer services companies.
A limited ability to estimate consumer spend behavior from point-in-time credit data has previously been available. A financial institution can, for example, simply monitor the balances of its own customers' accounts. When a credit balance is lowered, the financial institution could then assume that the corresponding consumer now has greater purchasing power. Such an assumption has its flaws, however. For example, it is oftentimes difficult to confirm whether the lowered balance is the result of a balance transfer to another account. Such balance transfers represent no increase in the consumer's capacity to spend, and so this simple model of consumer behavior has its flaws.
In order to achieve a complete picture of any consumer's purchasing ability and interests, one must examine in detail the full range of a consumer's financial accounts, including credit accounts, checking and savings accounts, investment portfolios, and the like. However, the vast majority of consumers do not maintain all such accounts with the same financial institution and the access to detailed financial information from other financial institutions is restricted by consumer privacy laws, disclosure policies and security concerns.
There is limited and incomplete consumer information from credit bureaus and the like at the aggregate and individual consumer levels. Since balance transfers are nearly impossible to consistently identify from the face of such records, this information has not previously been enough to obtain accurate estimates of a consumer's actual spending ability.
Accordingly, there is a need for a method and apparatus for determining a customer's size of wallet along with specific industries in which the customer is most likely to spend which addresses certain problems of existing technologies.